Monitoring habitat dynamics for rare and endangered species using satellite images and niche-based models

The potential distribution of critically rare or endangered species is necessary to assess species conservation status and guide recovery plans. Habitat models based on remotely sensed geospatial data are increasingly used to predict the suitability of sites for rare and endangered species, but in rapidly changing landscapes, habitat evaluations must reflect temporal as well as spatial variation of environmental suitability in order to properly inform management. We used field measurements of species occurrence, a 22-yr time series of satellite images, and the Maximum Entropy modeling approach (Maxent) to monitor spatio-temporal variation in habitat suitability of an endangered butterfly that uses riparian wetlands modified by beaver activity. We modeled the niche of the St. Francis' satyr Neonympha mitchellii francisci in an environment of remotely sensed metrics and projected the niche model over space and time to evaluate habitat dynamics and target sites for reintroduction efforts. Suitable habitat for the subspecies is currently distributed across the study area; however, most of the suitable area is unoccupied, and patches of the most suitable habitat have shifted over time in response to beaver activity and subsequent wetland succession, suggesting a negative interaction between dispersal limitation and landscape dynamics. Landcover changes complicate the recovery of critically threatened species such as N. m. francisci, but habitat monitoring over time can improve recovery plans, offer adaptive management strategies, and provide more exact criteria for species status assignment. Spatio-temporal extensions of the niche/habitat concept are made possible by long-term archives of remotely sensed data, and will likely prove most useful in rapidly changing landscapes.